docstr: Builds training graph for generator
  Arguments:
      disc_pred(object): Discriminator instance
docstr_tok: ["Builds","training","graph","for","generator","Arguments",":","disc_pred","(","object",")",":","Discriminator","instance"]
code: def build_train_graph(self, disc_pred):
      """
      Builds training graph for generator
      Arguments:
          disc_pred(object): Discriminator instance
  
      """
      # Variables in Mapper scope
      map_vars = tf.get_collection(
          tf.GraphKeys.TRAINABLE_VARIABLES, "Generator/Mapper"
      )
      # Binary Cross entropy
      map_entropy = tf.nn.sigmoid_cross_entropy_with_logits(
          logits=disc_pred, labels=(1 - self.Y)
      )
      # Cost
      map_cost = tf.reduce_mean(map_entropy)
      map_opt = tf.train.GradientDescentOptimizer(self.lr_ph)
      self.map_opt = map_opt.minimize(map_cost, var_list=map_vars)
  
imports: from __future__ import print_function, division
  import io
  import os
  import time
  import numpy
  import scipy
  import tensorflow
label_desc: Use image node_id 3 for calling the Generator obj's underlying member method code with example usage: obj.build_train_graph(disc_pred) without return types